Abstract:The increasing penetration of various distributed and renewable energy resources at the consumption premises, along with the advanced metering, control and communication technologies, promotes a transition on the structure of traditional distribution systems towards cyber-physical multi-microgrids (MMGs). The networked MMG system is an interconnected cluster of distributed generators, energy storage as well as controllable loads in a distribution system. And its operation complexity can be decomposed to decrease the burdens of communication and control with a decentralized framework. Consequently, the multi-microgrid energy management system (MMGEMS) plays a significant role in improving energy efficiency, power quality and reliability of distribution systems, especially in enhancing system resiliency during contingencies. A comprehensive overview on typical functionalities and architectures of MMGEMS is illustrated. Then, the emerging communication technologies for information monitoring and interaction among MMG clusters are surveyed. Furthermore, various energy scheduling and control strategies of MMGs for interactive energy trading, multi-energy management, and resilient operations are thoroughly analyzed and investigated. Lastly, some challenges with great importance in the future research are presented.

Abstract:Due to the tight coupling between the cyber and physical sides of a cyber-physical power system (CPPS), the safe and reliable operation of CPPSs is being increasingly impacted by cyber security. This situation poses a challenge to traditional security defense systems, which considers the threat from only one side, i.e., cyber or physical. To cope with cyber-attacks, this paper reaches beyond the traditional one-side security defense systems and proposes the concept of cyber-physical coordinated situation awareness and active defense to improve the ability of CPPSs. An example of a regional frequency control system is used to show the validness and potential of this concept. Then, the research framework is presented for studying and implementing this concept. Finally, key technologies for cyber-physical coordinated situation awareness and active defense against cyber-attacks are introduced.

Abstract:In this paper, we address the long-term generation and transmission expansion planning for power systems of regions with very high solar irradiation. We target the power systems that currently rely mainly on thermal generators and that aim to adopt high shares of renewable sources. We propose a stochastic programming model with expansion alternatives including transmission lines, solar power plants (photovoltaic and concentrated solar), wind farms, energy storage, and flexible combined cycle gas turbines. The model represents the long-term uncertainty to characterize the demand growth, and the short-term uncertainty to characterize daily solar, wind, and demand patterns. We use the Saudi Arabian power system to illustrate the functioning of the proposed model for several cases with different renewable integration targets. The results show that a strong dependence on solar power for high shares of renewable sources requires high generation capacity and storage to meet the night demand.

Abstract:As an aggregator of distributed energy resources (DERs) such as distributed generator, energy storage, and load, the virtual power plant (VPP) enables these small DERs participating in system operation. One of the critical issues is how to aggregate DERs to form VPPs appropriately. To improve the controllability and reduce the operation cost of VPP, the complementary DERs with close electrical distances should be aggregated in the same VPP. In this paper, it is formulated as an optimal network partition model for minimizing the voltage deviation inside VPPs and the fluctuation of injection power at the point of common coupling (PCC). A new convex formulation of network reconfiguration strategy is incorporated in this approach which can guarantee the components of the same VPP connected and further improve the performance of VPPs. The proposed approach is cast as an instance of mixed-integer linear programming (MILP) and can be effectively solved. Moreover, a scenario reduction method is developed to reduce the computation burden based on the k-shape algorithm. Numerical tests on the 13-bus and 70-bus distribution networks justify the effectiveness of the proposed approach.

Abstract:Active distribution grids cause bi-directional power flow between transmission system (TS) and distribution system (DS), which not only affects the optimal cost but also the secure operation of the power system. This paper proposes a hybrid coordination method to solve the risk-aware distributed optimal power flow (RA-DOPF) problem in coordinated TS and DS. For operation risk evaluation, the weather-based contingencies are considered in both TS and DS. A hybrid coordination method is developed that entails analytical target cascading (ATC) and Benders decomposition (BD). Moreover, the risk-aware optimal power flow (RAOPF) in TS and risk-based security-constrained optimal power flow in DS have been performed using the BD method considering basic optimal power flow as a master problem, whereas N-1 and N-2 contingencies are considered as sub-problems. Different case studies are performed using the IEEE 30-bus system with generation reserves as a TS and a 13-bus system as a DS. The results demonstrate the efficacy of the proposed method.

Abstract:Dynamic instability of decentralized wind energy farms is a major issue to deliver continuous green energy to electricity consumers. This instability is caused by variations of voltage and frequency parameters due to intermittencies in wind power. Previously, droop control and inverter-based schemes have been proposed to regulate the voltage by balancing reactive power, while inertial control, digital mapping technique of proportional-integral-differential (PID) controller and efficiency control strategy have been developed to regulate the frequency. In this paper, voltage stability is improved by a new joint strategy of distribution static compensator (DSTATCOM) six-pulse controller based reactive power management among decentralized wind turbines and controlled charging of capacitor bank. The frequency stability is ensured by a joint coordinated utilization of capacitor bank and distributed wind power turbines dispatching through a new DSTATCOM six-pulse controller scheme. In both strategies, power grid is contributed as a backup source with less priority. These new joint strategies for voltage and frequency stabilities will enhance the stable active power delivery to end users. A system test case is developed to verify the proposed joint strategies. The test results of the proposed new schemes are proved to be effective in terms of stability improvement of voltage, frequency and active power generation.

Abstract:We propose a new way to develop non-parametric models of power curves using artificial intelligence tools. One parametric model and eight non-parametric models are developed to emulate the behavior described by the power curve of the wind farms. A comparison between the power curve models based on artificial neural networks (ANNs) and those based on fuzzy logic are also proposed. Some of the power curve models based on ANNs and fuzzy inference systems (FISs) are used as well as two new FISs with the proposed new heuristic. An initial pre-training is proposed, resulting from the characteristics derived from the expert inference followed by a transformation of a fuzzy Mamdani system into a fuzzy Sugeno system. Although the presented values by the error indicators are comparable, the results show that the new pre-trained FIS models have better precision compared with the ANN and FIS models. The comparative study is conducted in two wind farms located in northeastern Brazil. The proposed method is a relevant alternative to improve power curve approximation based on an FIS.

Abstract:In this paper, a day-ahead electricity market bidding problem with multiple strategic generation company (GENCO) bidders is studied. The problem is formulated as a Markov game model, where GENCO bidders interact with each other to develop their optimal day-ahead bidding strategies. Considering unobservable information in the problem, a model-free and data-driven approach, known as multi-agent deep deterministic policy gradient (MADDPG), is applied for approximating the Nash equilibrium (NE) in the above Markov game. The MADDPG algorithm has the advantage of generalization due to the automatic feature extraction ability of the deep neural networks. The algorithm is tested on an IEEE 30-bus system with three competitive GENCO bidders in both an uncongested case and a congested case. Comparisons with a truthful bidding strategy and state-of-the-art deep reinforcement learning methods including deep Q network and deep deterministic policy gradient (DDPG) demonstrate that the applied MADDPG algorithm can find a superior bidding strategy for all the market participants with increased profit gains. In addition, the comparison with a conventional-model-based method shows that the MADDPG algorithm has higher computational efficiency, which is feasible for real-world applications.

Abstract:This paper proposes a simple and practical approach to model the uncertainty of solar irradiance and determines the optimized day-ahead (DA) schedule of electricity market. The problem formulation incorporates the power output of distributed solar photovoltaic generator (DSPVG) and forecasted load demands with a specified level of certainty. The proposed approach determines the certainty levels of the random variables (solar irradiance and forecasted load demand) from their probability density function curves. In this process of optimization, the energy storage system (ESS) has also been modeled based on the fact that the energy stored during low locational marginal price (LMP) periods and dispatched during high LMP periods would strengthen the economy of DA schedule. The objective of the formulated non-linear optimization problem is to maximize the social welfare of market participants, which incorporates the assured generation outputs of DSPVG, subject to real and reactive power balance and transmission capability constraints of the system and charging/discharging and energy storage constraints of ESS. The simulation has been performed on the Indian utility 62-bus system. The results are presented with a large number of cases to demonstrate the effectiveness of the proposed approach for the efficient, economic and reliable operation of DA electricity markets.

Abstract:Developing the electricity market at the distribution level can facilitate the energy transactions in distribution networks with a high penetration level of distributed energy resources (DERs) and microgrids (MGs). However, the lack of comprehensive information about the marginal production cost of competitors leads to uncertainties in the optimal bidding strategy of participants. The electricity demand within the network and the price in the wholesale electricity market are two other sources of the uncertainties. In this paper, a day-ahead-market-based framework for managing the energy transactions among MGs and other participants in distribution networks is introduced. A game-theory-based method is presented to model the competition and determine the optimal bidding strategy of participants in the market. Robust optimization technique is employed to capture the uncertainties in the marginal cost of competitors. Additionally, the uncertainties in demand are modeled using a scenario-based stochastic approach. The results obtained from case studies reveal the merit of considering competition modeling and uncertainties.

Abstract:A multi-agent consensus-based market scheme is proposed for the cooperation of community and multiple microgrids (MGs) in a distributed, economic and hierarchal manner. The proposed community-based market framework with frequency regulation (FR) market is formulated as a two-level scheduling problem: the global decision-making process of community agent (CA) to participate in the FR market and the interaction and control process of local MGs to achieve collaboration in response to the global target with efficient pricing rules. Specifically, the model predictive control (MPC) is integrated with the consensus-based theory to allow MG to obtain an economic and reliable dispatch in the presence of uncertainties of distributed generators and loads. Thanks to the distributed nature of the proposed scheme, its robustness to communication issues has been strengthened and a win-win situation for all energy stakeholders can be achieved. The robustness of the proposed scheme is investigated in various conditions, including different implementation strategies, communication topologies, and the level of uncertainties.

Abstract:Innovative advancement in power electronics is reshaping the conventional high-voltage transmission systems and has also opened a new paradigm for researchers to consider its benefits in the railway electrification system (RES). In this regard, the medium-voltage direct current RES (MVDC-RES) is a key area of interest nowadays. In this paper, a secondary energy source (SES) consisting of renewable energies (REs) and energy storage systems (ESSs) is proposed to solve the issues of catenary voltage regulation, rail potential, and stray current in the MVDC-RES. Some of the major integration topologies of the SES are analyzed for MVDC-RES and the most effective one is proposed and implemented. The voltage at the point of connection (PoC) of the SES is used as a reference for controlling different operation modes of REs and ESSs. Moreover, feedforward control is used at the ESS converter to attain the quick response from the batteries for the desired operation. The proposed scheme improves the catenary voltage, and reduces the rail potential and stray current. Besides, the scheme provides higher energy density and reduces line losses. Simulation results are provided to validate the operation modes and advantages of the proposed scheme.

Abstract:This paper investigates the impact of electric vehicle (EV) aggregator with communication time delay on stability regions and stability delay margins of a single-area load frequency control (LFC) system. Primarily, a graphical method characterizing stability boundary locus is implemented. For a given time delay, the method computes all the stabilizing proportional-integral (PI) controller gains, which constitutes a stability region in the parameter space of PI controller. Secondly, in order to complement the stability regions, a frequency-domain exact method is used to calculate stability delay margins for various values of PI controller gains. The qualitative impact of EV aggregator on both stability regions and stability delay margins is thoroughly analyzed and the results are authenticated by time-domain simulations and quasi-polynomial mapping-based root finder (QPmR) algorithm.

Abstract:The traffic and user have significant impacts on the electric vehicle (EV) charging load but are not considered in the existing research. We propose a novel integrated simulation framework considering the traffic, the user, and power grid as well as the EV traveling, parking and charging based on cellular automaton (CA). The traffic is modeled by the traffic module of the proposed framework based on CA, while the power grid and user are modeled in the EV charging module. The traffic flow, user’s charging preference, user’s charging satisfaction, and the total supply capability (TSC) in the surveyed region are considered in the proposed framework. Two cases are carried out to show the interactions between the user and power grid. It is shown that the proposed framework can accurately simulate the interactions among traffic situation, user’s behavior and TSC， which are significantly lacking in the existing research. The proposed framework is scalable in considering additional interrelated elements.

Abstract:Due to the high penetration of renewable distributed generation (RDG), many issues have become conspicuous during the intentional island operation such as the power mismatch of load shedding during the transition process and the power imbalance during the restoration process. In this paper, a phase measurement unit (PMU) based online load shedding strategy and a conservation voltage reduction (CVR) based multi-period restoration strategy are proposed for the intentional island with RDG. The proposed load shedding strategy, which is driven by the blackout event, consists of the load shedding optimization and correction table. Before the occurrence of the large-scale blackout, the load shedding optimization is solved periodically to obtain the optimal load shedding plan, which meets the dynamic and steady constraints. When the blackout occurs, the correction table updated in real time based on the PMU data is used to modify the load shedding plan to eliminate the power mismatch caused by the fluctuation of RDG. After the system transits to the intentional island seamlessly, multi-period restoration plans are generated to optimize the restoration performance while maintaining power balance until the main grid is repaired. Besides, CVR technology is implemented to restore more loads by regulating load demand. The proposed load shedding optimization and restoration optimization are linearized to mixed-integer quadratic constraint programming (MIQCP) models. The effectiveness of the proposed strategies is verified with the modified IEEE 33-node system on the real-time digital simulation (RTDS) platform.

Abstract:The power demand around the world is increasing rapidly. The aging distribution network architectures are used by the existing utility companies to deliver power to the consumers, which significantly affects the reliability, stability and quality of the delivered power. Different techniques such as compensation devices have been used by power system engineers and researchers to maintain the quality of power transmitted to end users. In this paper, wattage and volt-amp reactive (VAR) planning scheme has been proposed by using the combination of battery energy storage systems (BESS) and compensators to deal with the vulnerability of networks to voltage drop and system inefficiency. The cost-effective combination of BESS and shunt capacitor bank will then be analyzed to indicate the benefit of the proposed scheme.

Abstract:The impact of voltage sag on sensitive devices is related to the time when the sag occurs. However, the point-on-wave of a sag is uncertain. Therefore, this paper presents a novel approach to evaluate the voltage sag severity considering a random point-on-wave. First, the uncertainty of equipment malfunction is revealed. Second, under a given residual voltage, the relationship between the point-on-wave and the duration that the device can withstand is described with a fitting curve. Third, a voltage sag probabilistic index is proposed to describe the severity. The evaluation procedure is also presented. Finally, three types of releasers are tested and analyzed to determine the effectiveness of the proposed method. The evaluation method can help instruct electrical engineers establish more well-grounded sag mitigation proposals.

Abstract:The dynamic characteristics of converter-dominated systems are governed by controlling power converters and the interactions between converter systems and conventional alternators. Frequency oscillations can appear under dynamic operation conditions caused by the phase-locked loop dynamics and interactions among the converter control systems. The oscillations may be poorly damped, which can result in reduced power generation, longer settling time, or disconnections of sensitive components. It is foreseeable that damping services will be critical for power grid stabilization in the future with high penetration of renewable generation. In this work, synchronous condensers (SCs) are evaluated and applied to provide damping services to the power grid under post-event conditions. An innovative supplementary controller for the automatic voltage regulator of SCs is proposed to improve the frequency stabilization in a converter-dominated system after disturbances. Using local and remote measurements, SCs are able to modulate the reactive power output and hence, the terminal bus voltage, which further impacts the power flow in the system; therefore, damping can be provided to the frequency oscillations. The control is implemented on an industrial-level hardware platform, and the performance is verified by the hardware-in-the-loop simulation.

Abstract:Environmental and electrical factors such as wind speed, air temperature and switching frequency have significant influences on the operational reliability of hybrid modular multilevel converter (MMC), which is commonly used for the wind power transmission. However, the existing reliability model of hybrid MMC based on statistics cannot accurately reflect the impact of these factors. In this paper, a new operational reliability model of hybrid MMC is presented. The reliability index of the hybrid MMC is coupled with its operation characteristics by calculating multi-term thermal cycling. In addition, an operation strategy of hybrid MMC is proposed to improve its reliability. The multi-state submodule (SM) is developed, which is capable of bypassing specific faulty power modules instead of the whole SM. Case studies show that the proposed operational reliability model could describe the impact of environmental and electrical factors. Also, the proposed operation strategy can improve the reliability of hybrid MMC by extending the operation time of SMs.

Abstract:We propose a modular multilevel converter (MMC) based three-phase four-wire (3P4W) split capacitor distribution static synchronous compensator (DSTATCOM), aiming at compensating unbalanced and reactive load currents. Due to the zero-sequence current compensation, the circulating current characteristics of 3P4W MMC-DSTATCOM are different from conventional MMCs. Moreover, the distinct working principle of MMC would affect the features of split capacitor voltage. The decoupled positive-, negative- and zero-sequence second-order and DC components of the circulating current are deduced explicitly. Two proportional-integral controllers with dual dq transformation are employed to suppress the positive- and negative-sequence components of second-order circulating current, while quasi proportional-resonance controller is designed to eliminate the zero-sequence component. Besides, the phenomenon of the unbalanced split capacitor voltages is revealed, and fast-tracking balancing method by controlling zero-sequence current flowing through the split capacitors is provided. Digital simulation results verify the accuracy of the analysis and the feasibility of the suppression methods.

Abstract:This paper proposes a sliding mode controller based on robust model reference adaptive proportional-integral (RMRA-PI) control for a stand-alone voltage source inverter (SA-VSI). The proposed controller has two control loops where the coefficients of PI controller are regulated by the adaptive sliding law. This method is used to regulate the output voltage of the inverter under different load conditions and uncertainty, and adapts the output to the reference model to reduce the total harmonic distortion (THD). In this paper, the stability of the proposed controller is proven by using Lyapunov’s theory and Barbalet’s lemma. The proposed controller performs well in voltage regulation such as low THD under sudden load change and uncertainty. Also, the results of the proposed controller are compared with PI controller to show the effectiveness of the presented control system.

Abstract:A quasi-linear relationship between voltage angles and voltage magnitudes in power flow calculation is presented. An accurate estimation of voltage magnitudes can be provided by the quasi-linear relationship when voltage angles are derived by classical DC power flow. Based on the quasi-linear relationship, a novel extended DC power flow (EDCPF) model is proposed considering voltage magnitudes. It is simple, reliable and accurate for both distribution network and transmission network in normal system operation states. The accuracy of EDCPF model is verified through a series of standard test systems.

Abstract:This letter presents a systematic approach to estimate the annual energy production (AEP) of variable-speed wind turbines erected at high-altitude sites. Compared with the existing empirical-model based approaches, the proposed approach models the influence of the air density on the power production while employing the theoretical power curve. Consequently, the proposed approach provides a precise estimation of AEP, which can serve as a foundation of the optimum turbine-site matching design at different-altitude sites.